Antik Chakraborty

Antik Chakraborty

Assistant Professor

Department of Statistics
Purdue University

Preprints

  1. Tong, R., Chakraborty, A., & Pasupathy, R. (2026). Two-Loop Stochastic Mirror Langevin Algorithms for Constrained Sampling. Preprint. arXiv Code

  2. Chen, Y., Chakraborty, A., & Bhadra, A. (2026). Covariate-dependent Joint Modeling of Multivariate Ordinal Preferences and Its Connections with Comparison Models. Preprint. arXiv Code

  3. Xu, M., Chakraborty, A., & Xu, Y. (2025). A Bayesian Clustering Approach to Multi-Population Mortality Modeling and Forecasting. Working paper. Paper

Publications

  1. Tong, R., Chakraborty, A., & Pasupathy, R. (2026). Mirror Langevin Markov Chain Monte Carlo for Constrained Random Variate Generation. Proceedings of the 2026 Winter Simulation Conference, forthcoming.

  2. Chakraborty, A., & Xue, F. (2026). Empirical Bayes Data Integration for Multi-Response Regression. Statistica Sinica, forthcoming. Paper Code DOI

  3. Chen, Y., Chakraborty, A., & Bhadra, A. (2026). Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model. Proceedings of the 29th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 300, 3376-3384. Paper arXiv Code

  4. Chen, Y., Bhadra, A., & Chakraborty, A. (2026). Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing Constants. Journal of Machine Learning Research, to appear. arXiv Code

  5. Chakraborty, A., Walsh, J. L., Strigari, L., Mallick, B. K., & Bhattacharya, A. (2026). Orthogonal Calibration Via Posterior Projections with Applications to the Schwarzschild Model. Technometrics, 68(1), 14-23. Paper arXiv Code DOI

  6. Eschker, S. J., Chakraborty, A., Gall, M., Jevtic, P., & Su, J. (2026). State Space Modeling of Mortgage Default Rates Under Natural Hazard Shocks. North American Actuarial Journal, 30(3), 662-678. Paper arXiv DOI

  7. Chakraborty, A., Ou, R., & Dunson, D. B. (2024). Bayesian Inference on High-Dimensional Multivariate Binary Responses. Journal of the American Statistical Association, 119(548), 2560-2571. Paper arXiv Code DOI

  8. Chattopadhyay, S., Chakraborty, A., & Dunson, D. B. (2023). Nearest Neighbor Dirichlet Mixtures. Journal of Machine Learning Research, 24(261), 1-46. Paper arXiv Code

  9. Chakraborty, A., Ovaskainen, O., & Dunson, D. B. (2022). Bayesian Semiparametric Long Memory Models for Discretized Event Data. The Annals of Applied Statistics, 16(3), 1380-1399. Paper arXiv Code DOI

  10. Chakraborty, A., Bhattacharya, A., & Mallick, B. K. (2020). Bayesian Sparse Multiple Regression for Simultaneous Rank Reduction and Variable Selection. Biometrika, 107(1), 205-221. Paper arXiv Code DOI

  11. Sarkar, A., Pati, D., Chakraborty, A., Mallick, B. K., & Carroll, R. J. (2018). Bayesian Semiparametric Multivariate Density Deconvolution. Journal of the American Statistical Association, 113(521), 401-416. Paper arXiv DOI

  12. Jain, P., Chakraborty, A., Pistikopoulos, E. N., & Mannan, M. S. (2018). Resilience-Based Process Upset Event Prediction Analysis for Uncertainty Management Using Bayesian Deep Learning: Application to a Polyvinyl Chloride Process System. Industrial & Engineering Chemistry Research, 57(43), 14822-14836. Paper DOI

  13. Bhattacharya, A., Chakraborty, A., & Mallick, B. K. (2016). Fast Sampling with Gaussian Scale Mixture Priors in High-Dimensional Regression. Biometrika, 103(4), 985-991. Paper arXiv Code DOI